Progress toward all-digital medical imaging environments has substantially increased the speed at which large amounts of medical image information can be accessed and displayed to a radiologist. As used herein, radiologist generically refers to a medical professional that analyzes medical images and makes clinical determinations therefrom, it being understood that such person might be titled differently, or might have differing qualifications, depending on the country or locality of their particular medical environment.
One example of the increasing amount of information available to the radiologist relates to the temporal comparison of mammographic images, wherein years of prior mammographic images may be available for viewing in conjunction with a current-year mammographic image. However, as discussed in the commonly-assigned U.S. Ser. 11/173,960, entitled “Displaying and Navigating Computer-Aided Detection Results on a Review Workstation,” which is incorporated by reference herein, problems can arise at the interface between (a) the amount of information available to a radiologist, and (b) the amount of information that can be usefully perceived by the radiologist in a reasonable amount of time. These issues are especially important in today's radiology environment, where there is an ongoing tension between providing high-quality detection/diagnosis for each patient and maintaining adequate patient throughput to keep costs under control. Even the differences between a few hand movements, keystrokes, or mouse cursor movements can lead to substantial changes in radiologist efficiency, stamina, and/or accuracy, which can save lives.
The term computer-aided detection (CAD) is commonly used to refer to the use of computers to analyze medical images to detect anatomical abnormalities therein, and/or the use of computers to otherwise process image information in a manner that facilitates perception of the medical image information by a radiologist. Sometimes used interchangeably with the term computer-aided detection are the terms computer-aided diagnosis, computer-assisted diagnosis, or computer-assisted detection. In an abnormality detection context, a CAD algorithm usually identifies a preliminary set of candidate detections in a medical image and then selects which ones, if any, will qualify as actual CAD detections based on a variety of computed features associated with the candidate detections. The CAD results, i.e., the body of information associated with the operation of the CAD algorithm on the medical image, are most often communicated in the form of annotation maps comprising graphical annotations (CAD markers) overlaid on a diagnostic-quality or reduced-resolution version of the medical image, one CAD marker for each CAD detection. Substantial effort and attention has been directed to increasing the analysis capabilities of CAD systems, resulting in ever-increasing amounts of information that is available to the radiologist for review.
For the important context of temporal comparison, at least one of the preferred embodiments herein is not necessarily directed to providing more CAD-generated information to the radiologist, but rather to providing better presentation of medical image information that already needs to be presented to the radiologist. As known in the art, there are often many different commercial image acquisition and display systems available for use. Examples for the digital mammography field include Senographe 2000D (General Electric), Senoscan (Fischer), Selenia (Lorad, a Hologic Company), Microdose (Sectra), FCR Profect (Fuji), CR 85.0 (Agfa), CR 850/950 (Kodak), Regius 190 (Konica), and Novation (Siemens). Generally speaking, the various image acquisition and display systems can have significantly different detector sizes, detector spatial resolutions, and detector characteristic response curves, as well as different display monitor types and display enhancement algorithms. Also, there are many different analog (film-based) mammography systems in use, and many different types of digitizers available for scanning the resultant film images into digital format for processing, display, and/or archiving.
It can often be the case that a prior year mammogram was obtained using a first type of image acquisition and display system and a subsequent year mammogram was obtained using a second type of image acquisition and display system, whereas the prior and subsequent year mammograms are being presented side-by-side for temporal comparison on only one of the first or second display systems, or on an altogether different third display system. Problems can arise in this side-by-side display that can adversely affect the radiologist experience, such as a need to repeatedly shift, re-window, or re-size the images, a need to repeatedly change brightness/contrast settings, etc., so that the prior and subsequent-year mammograms can be properly viewed for comparison. This can bring about reduced radiologist efficiency, increased irritation or fatigue, or even missed detections or incorrect diagnoses resulting from the different size, scale, windowing, or otherwise different look of the side-by-side images not sufficiently corrected or correctable by the radiologist. It would be desirable to provide for processing of the prior and/or subsequent year medical images for side-by-side comparison in a manner that at least partially resolves one or more of the above issues.
Although the preferred embodiments described herein are particularly advantageous in an x-ray mammography environment and are presented in such context, it is to be appreciated that the features and advantages of the preferred embodiments can also be applied in other medical imaging contexts including, but not limited to, ultrasound, x-ray tomosynthesis, CT, MRI, PET, SPECT, thermography, electrical conductivity-based modalities, and other modalities for a variety of different body parts (e.g., head, neck, chest, abdomen, etc.). Other issues arise as would be apparent to one skilled in the art upon reading the present disclosure.